Multivariate decision and detection limits

✍ Scribed by Anita Singh

• Publisher: Elsevier Science
• Year: 1993
• Tongue: English
• Weight: 865 KB
• Volume: 277
• Category: Article
• ISSN: 0003-2670
• DOI: 10.1016/0003-2670(93)80434-m

✦ Synopsis

Principal component analysis (PCA) is used to develop an approach for estimating multivariate decision and detection limits (MDDLs) for gas chromatography-mass spectrometry studies where the instrument response is multivariate in nature. Many definitions and estimators have been published for univariate responses. In this article we extend these ideas to the multivariate case. When the first principal component explains most of the variation contained in the data, it may be used to express the multicomponent instrumental response as a univariate composite signal representing all of the monitored ions associated with the analyte of interest. The first principal component of these ions has been used to derive decision and detection limits through two approaches. Back-transformation of this composite instrument response to the original response variables will yield multivariate decision and detection limits for all of the ions considered shnultaneously.